Notice: Function _load_textdomain_just_in_time was called incorrectly. Translation loading for the imagemagick-engine domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /usr/local/data/sites/proginres/htdocs-SSL/wp-includes/functions.php on line 6121

Notice: La funzione _load_textdomain_just_in_time è stata richiamata in maniera scorretta. Il caricamento della traduzione per il dominio ct è stato attivato troppo presto. Di solito è un indicatore di un codice nel plugin o nel tema eseguito troppo presto. Le traduzioni dovrebbero essere caricate all'azione init o in un secondo momento. Leggi Debugging in WordPress per maggiori informazioni. (Questo messaggio è stato aggiunto nella versione 6.7.0.) in /usr/local/data/sites/proginres/htdocs-SSL/wp-includes/functions.php on line 6121
How can we support healthcare workers to avoid burnout? – Progress in Research
22/02/2022

How can we support healthcare workers to avoid burnout?

A research paper by the politecnico published in the journal of biomedical informatics

By placing enormous pressure on healthcare workers, the COVID-19 pandemic has put doctors, nurses and hospital staff at the risk of developing psychological problems (burnout, Post-Traumatic Stress Disorder).

The Politecnico di Milano, in collaboration with the psychologists at the Università degli Studi di Milano and the Istituti Clinici Maugeri, has carried out in-dept analysis of the answers given in a questionnaire handed out to Italian healthcare workers during the first wave of the pandemic (April-May 2020).

The data gathered, regarding socio-demographics, lifestyle, working conditions, COVID-19-related health conditions and psychological indicators, were subsequently analysed using innovative data science methods that enabled different risk profiles to be associated with the various subgroups into which the sample was divided.

Published in the prestigious Journal of Biomedical Informatics, this study forms a basis for the implementation of self-diagnosis apps specifically for healthcare workers subjected to high-risk conditions that allow personalised psychological measures to be taken during pandemic situations.

Enrico Caiani and Emanuele TauroDepartment of Electronics, Information and Bioengineering at Politecnico di Milano, are two of the authors of this article.

Life Sciences

You may also be interested in

Questo sito utilizza i cookies per le statistiche e per agevolare la navigazione nelle pagine del sito e delle applicazioni web. Maggiori informazioni sono disponibili alla pagina dell'informativa sulla privacy

Accetto